60 lines
2 KiB
Python
60 lines
2 KiB
Python
# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
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#
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# NVIDIA CORPORATION and its licensors retain all intellectual property
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# and proprietary rights in and to this software, related documentation
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# and any modifications thereto. Any use, reproduction, disclosure or
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# distribution of this software and related documentation without an express
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# license agreement from NVIDIA CORPORATION is strictly prohibited.
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"""Fused multiply-add, with slightly faster gradients than `torch.addcmul()`."""
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import torch
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#----------------------------------------------------------------------------
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def fma(a, b, c): # => a * b + c
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return _FusedMultiplyAdd.apply(a, b, c)
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#----------------------------------------------------------------------------
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class _FusedMultiplyAdd(torch.autograd.Function): # a * b + c
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@staticmethod
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def forward(ctx, a, b, c): # pylint: disable=arguments-differ
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out = torch.addcmul(c, a, b)
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ctx.save_for_backward(a, b)
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ctx.c_shape = c.shape
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return out
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@staticmethod
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def backward(ctx, dout): # pylint: disable=arguments-differ
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a, b = ctx.saved_tensors
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c_shape = ctx.c_shape
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da = None
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db = None
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dc = None
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if ctx.needs_input_grad[0]:
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da = _unbroadcast(dout * b, a.shape)
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if ctx.needs_input_grad[1]:
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db = _unbroadcast(dout * a, b.shape)
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if ctx.needs_input_grad[2]:
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dc = _unbroadcast(dout, c_shape)
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return da, db, dc
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#----------------------------------------------------------------------------
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def _unbroadcast(x, shape):
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extra_dims = x.ndim - len(shape)
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assert extra_dims >= 0
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dim = [i for i in range(x.ndim) if x.shape[i] > 1 and (i < extra_dims or shape[i - extra_dims] == 1)]
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if len(dim):
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x = x.sum(dim=dim, keepdim=True)
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if extra_dims:
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x = x.reshape(-1, *x.shape[extra_dims+1:])
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assert x.shape == shape
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return x
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#----------------------------------------------------------------------------
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